simaerep {simaerep}

create simaerep object

Description

simulate AE under-reporting probabilities

Usage

simaerep(
  df_visit,
  param_site_aggr = list(method = "med75_adj", min_pat_pool = 0.2),
  param_sim_sites = list(r = 1000, poisson_test = FALSE, prob_lower = TRUE),
  param_eval_sites = list(method = "BH"),
  progress = TRUE,
  check = TRUE,
  env = parent.frame(),
  under_only = TRUE
)

Arguments

df_visit

data frame with columns: study_id, site_number, patnum, visit, n_ae

param_site_aggr

list of parameters passed to site_aggr(), Default: list(method = "med75_adj", min_pat_pool = 0.2)

param_sim_sites

list of parameters passed to sim_sites(), Default: list(r = 1000, poisson_test = FALSE, prob_lower = TRUE)

param_eval_sites

list of parameters passed to eval_sites(), Default: list(method = "BH")

progress

logical, display progress bar, Default = TRUE

check

logical, perform data check and attempt repair with check_df_visit(), computationally expensive on large data sets. Default: TRUE

env

optional, provide environment of original visit data, Default: parent.frame()

under_only

logical compute under-reporting probabilities only, superseeds under_only parameter passed to eval_sites() and sim_sites(), Default: TRUE

Details

executes site_aggr(), sim_sites() and eval_sites() on original visit data and stores all intermediate results. Stores lazy reference to original visit data for facilitated plotting using generic plot(x).

Value

simaerep object

See Also

site_aggr(), sim_sites(), eval_sites(), orivisit(), plot.simaerep()

Examples

df_visit <- sim_test_data_study(
  n_pat = 100,
  n_sites = 5,
  frac_site_with_ur = 0.4,
  ur_rate = 0.6
)

df_visit$study_id <- "A"

aerep <- simaerep(df_visit)

aerep

str(aerep)